As data volume and broadband network speeds continue to increase, more and more computer users are turning to distributed data storage systems to satisfy their data storage needs. Distributed data storage systems include data storage hardware located at multiple nodes, where the nodes are often at different physical locations. Examples of distributed data storage systems include many popularly available cloud storage solutions for organizations and individuals.
In distributed storage systems, read time often an important measure of performance. Users expect to receive their data quickly. Some distributed storage systems increase data read time using hardware, such as disks or other data storage, network hardware, etc. Faster hardware on the storage side can lead to faster read times for users. Faster hardware, however, is typically also more expensive. Accordingly, many distributed storage system utilizing hardware tiering.
In some scenarios, hot data that is accessed frequently is stored using faster hardware. Warm data that is accessed less frequently is stored using slightly slower hardware. Cold data that is seldom accessed is stored using slower, less-expensive hardware. As hot data cools (e.g., is accessed less frequently), it is dynamically moved to slower hardware. This approach requires faster and more expensive hardware for storing hot data. It also requires careful hardware management. For example, if the volume of hot data increases, more fast hardware must be added to the system.